A Comparative Genomics Analysis of Codon Reassignments Reveals a Link with Mitochondrial Proteome Size and a Mechanism of Genetic Code Change Via Suppressor tRNAs

Using a comparative genomics approach we demonstrate a negative correlation between the number of codon reassignments undergone by 222 mitochondrial genomes and the mitochondrial genome size, the number of mitochondrial ORFs, and the sizes of the large and small subunit mitochondrial rRNAs. In addition, we show that the TGA-to-tryptophan codon reassignment, which has occurred 11 times in mitochondrial genomes, is found in mitochondrial genomes smaller than those which have not undergone the reassignment. We therefore propose that mitochondrial codon reassignments occur in a wide range of phyla, particularly in Metazoa, due to a reduced “proteomic constraint” on the mitochondrial genetic code, compared to the nuclear genetic code. The reduced proteomic constraint reflects the small size of the mitochondrial-encoded proteome and allows codon reassignments to occur with less likelihood of lethality. In addition, we demonstrate a striking link between nonsense codon reassignments and the decoding properties of naturally occurring nonsense suppressor tRNAs. This suggests that natural preexisting nonsense suppression facilitated nonsense codon reassignments and constitutes a novel mechanism of genetic code change. These findings explain for the first time the identity of the stop codons and amino acids reassigned in mitochondrial and nuclear genomes. Nonsense suppressor tRNAs provided the raw material for nonsense codon reassignments, implying that the properties of the tRNA anticodon have dictated the identity of nonsense codon reassignments. Electronic Supplementary Material The online version of this article (doi:) contains supplementary material, which is available to authorized users. [Reviewing Editor: Dr. Laura Landweber]     

The distribution of recombination repair genes is linked to information content in bacteria

The concept of a ‘proteomic constraint’ proposes that the information content of the proteome exerts a selective pressure to reduce mutation rates, implying that larger proteomes produce a greater selective pressure to evolve or maintain DNA repair, resulting in a decrease in mutational load. Here, the distribution of 21 recombination repair genes was characterized across 900 bacterial genomes. Consistent with prediction, the presence of 17 genes correlated with proteome size. Intracellular bacteria were marked by a pervasive absence of recombination repair genes, consistent with their small proteome sizes, but also consistent with alternative explanations that reduced effective population size or lack of recombination may decrease selection pressure. However, when only non-intracellular bacteria were examined, the relationship between proteome size and gene presence was maintained. In addition, the more widely distributed (i.e. conserved) a gene, the smaller the average size of the proteomes from which it was absent. Together, these observations are consistent with the operation of a proteomic constraint on DNA repair. Lastly, a correlation between gene absence and genome AT content was shown, indicating a link between absence of DNA repair and elevated genome AT content.     

Critical Mutation Rate Has an Exponential Dependence on Population Size in Haploid and Diploid Populations

Understanding the effect of population size on the key parameters of evolution is particularly important for populations nearing extinction. There are evolutionary pressures to evolve sequences that are both fit and robust. At high mutation rates, individuals with greater mutational robustness can outcompete those with higher fitness. This is survival-of-the-flattest, and has been observed in digital organisms, theoretically, in simulated RNA evolution, and in RNA viruses. We introduce an algorithmic method capable of determining the relationship between population size, the critical mutation rate at which individuals with greater robustness to mutation are favoured over individuals with greater fitness, and the error threshold. Verification for this method is provided against analytical models for the error threshold. We show that the critical mutation rate for increasing haploid population sizes can be approximated by an exponential function, with much lower mutation rates tolerated by small populations. This is in contrast to previous studies which identified that critical mutation rate was independent of population size. The algorithm is extended to diploid populations in a system modelled on the biological process of meiosis. The results confirm that the relationship remains exponential, but show that both the critical mutation rate and error threshold are lower for diploids, rather than higher as might have been expected. Analyzing the transition from critical mutation rate to error threshold provides an improved definition of critical mutation rate. Natural populations with their numbers in decline can be expected to lose genetic material in line with the exponential model, accelerating and potentially irreversibly advancing their decline, and this could potentially affect extinction, recovery and population management strategy. The effect of population size is particularly strong in small populations with 100 individuals or less; the exponential model has significant potential in aiding population management to prevent local (and global) extinction events.     

Genetic progression and the waiting time to cancer

Cancer results from genetic alterations that disturb the normal cooperative behavior of cells. Recent high-throughput genomic studies of cancer cells have shown that the mutational landscape of cancer is complex and that individual cancers may evolve through mutations in as many as 20 different cancer-associated genes. We use data published by Sjöblom et al. (2006) to develop a new mathematical model for the somatic evolution of colorectal cancers. We employ the Wright-Fisher process for exploring the basic parameters of this evolutionary process and derive an analytical approximation for the expected waiting time to the cancer phenotype. Our results highlight the relative importance of selection over both the size of the cell population at risk and the mutation rate. The model predicts that the observed genetic diversity of cancer genomes can arise under a normal mutation rate if the average selective advantage per mutation is on the order of 1%. Increased mutation rates due to genetic instability would allow even smaller selective advantages during tumorigenesis. The complexity of cancer progression can be understood as the result of multiple sequential mutations, each of which has a relatively small but positive effect on net cell growth.     

Why mitochondrial genes are most often found in nuclei

A very small fraction of the proteins required for the propagation and function of mitochondria are coded by their genomes, while nuclear genes code the vast majority. We studied the migration of genes between the two genomes when transfer mechanisms mediate this exchange. We could calculate the influence of differential mutation rates, as well as that of biased transfer rates, on the partitioning of genes between the two genomes. We observe no significant difference in partitioning for haploid and diploid cell populations, but the effective size of cell populations is important. For infinitely large effective populations, higher mutation rates in mitochondria than in nuclear genomes are required to drive mitochondrial genes to the nuclear genome. In the more realistic case of finite populations, gene transfer favoring the nucleus and/or higher mutation rates in the mitochondrion will drive mitochondrial genes to the nucleus. We summarize experimental data that identify a gene transfer process mediated by vacuoles that favors the accumulation of mitochondrial genes in the nuclei of modern cells. Finally, we compare the behavior of mitochondrial genes for which transfer to the nucleus is neutral or influenced by purifying selection.     

The evolution of biased codon and amino acid usage in nematode genomes

Despite the degeneracy of the genetic code, whereby different codons encode the same amino acid, alternative codons and amino acids are utilized nonrandomly within and between genomes. Such biases in codon and amino acid usage have been demonstrated extensively in prokaryote genomes and likely reflect a balance between the action of mutation, selection, and genetic drift. Here, we quantify the effects of selection and mutation drift as causes of codon and amino acid-usage bias in a large collection of nematode partial genomes from 37 species spanning approximately 700 Myr of evolution, as inferred from expressed sequence tag (EST) measures of gene expression and from base composition variation. Average G + C content at silent sites among these taxa ranges from 10% to 63%, and EST counts range more than 100-fold, underlying marked differences between the identities of major codons and optimal codons for a given species as well as influencing patterns of amino acid abundance among taxa. Few species in our sample demonstrate a dominant role of selection in shaping intragenomic codon-usage biases, and these are principally free living rather than parasitic nematodes. This suggests that deviations in effective population size among species, with small effective sizes among parasites, are partly responsible for species differences in the extent to which selection shapes patterns of codon usage. Nevertheless, a consensus set of optimal codons emerges that is common to most taxa, indicating that, with some notable exceptions, selection for translational efficiency and accuracy favors similar sets of codons regardless of the major codon-usage trends defined by base compositional properties of individual nematode genomes.     

Effect of Correlated tRNA Abundances on Translation Errors and Evolution of Codon Usage Bias

Despite the fact that tRNA abundances are thought to play a major role in determining translation error rates, their distribution across the genetic code and the resulting implications have received little attention. In general, studies of codon usage bias (CUB) assume that codons with higher tRNA abundance have lower missense error rates. Using a model of protein translation based on tRNA competition and intra-ribosomal kinetics, we show that this assumption can be violated when tRNA abundances are positively correlated across the genetic code. Examining the distribution of tRNA abundances across 73 bacterial genomes from 20 different genera, we find a consistent positive correlation between tRNA abundances across the genetic code. This work challenges one of the fundamental assumptions made in over 30 years of research on CUB that codons with higher tRNA abundances have lower missense error rates and that missense errors are the primary selective force responsible for CUB.     

Clonal interference is alleviated by high mutation rates in large populations

When a beneficial mutation is fixed in a population that lacks recombination, the genetic background linked to that mutation is fixed. As a result, beneficial mutations on different backgrounds experience competition, or "clonal interference," that can cause asexual populations to evolve more slowly than their sexual counterparts. Factors such as a large population size (N) and high mutation rates (mu) increase the number of competing beneficial mutations, and hence are expected to increase the intensity of clonal interference. However, recent theory suggests that, with very large values of Nmu, the severity of clonal interference may instead decline. The reason is that, with large Nmu, genomes including both beneficial mutations are rapidly created by recurrent mutation, obviating the need for recombination. Here, we analyze data from experimentally evolved asexual populations of a bacteriophage and find that, in these nonrecombining populations with very large Nmu, recurrent mutation does appear to ameliorate this cost of asexuality.     

Driving change: the evolution of alternative genetic codes

Pioneering studies in the 1960s that elucidated the genetic code suggested that all extant forms of life use the same genetic code. This early presumption has subsequently been challenged by the discovery of deviations of the universal genetic code in prokaryotes, eukaryotic nuclear genomes and mitochondrial genomes. These studies have revealed that the genetic code is still evolving despite strong negative forces working against the fixation of mutations that result in codon reassignment. Recent data from in vitro, in vivo and in silico comparative genomics studies are revealing significant, previously overlooked links between modified nucleosides in tRNAs, genetic code ambiguity, genome base composition, codon usage and codon reassignment.     

Microsatellites, transposable elements and the X chromosome

Variability at microsatellite (MS) loci is generally perceived as resulting from an interaction between mutation and genetic drift and, to a lesser extent, selection and recombination. Less investigated has been the reason for MS accumulation in genomes. We present here a simple model that could account for the variation in density of MS loci, assuming that they are created either through replication slippage or in association with transposable elements. Microsatellites then evolve under the forces cited above. We use this framework to revisit two results obtained from high-density genomic maps of the human and mouse genomes built with thousands of CA repeats: MS loci are (1) less variable and (2) less dense on the X chromosome than on autosomes. The first result is most likely explained by differential mutation on the X chromosome and the autosomes. The second result may be explained by differential mutation, provided the distributions of MS loci are still not at equilibrium. Selection, acting either directly on large allele size or indirectly on the transposable elements associated with MS, may explain the same result. The framework developed here is a first step toward more rigorous models, calling for additional data.      

Evolutionary Aspects of Functional and Pseudogene Members of the Phytochrome Gene Family in Scots Pine

According to the neutral theory of evolution, mutation and genetic drift are the only forces that shape unconstrained, neutral, gene evolution. Thus, pseudogenes (which often evolve neutrally) provide opportunities to obtain direct estimates of mutation rates that are not biased by selection, and gene families comprising functional and pseudogene members provide useful material for both estimating neutral mutation rates and identifying sites that appear to be under positive or negative selection pressures. Conifers could be very useful for such analyses since they have large and complex genomes. There is evidence that pseudogenes make significant contributions to the size and complexity of gene families in pines, although few studies have examined the composition and evolution of gene families in conifers. In this work, I examine the complexity and rates of mutation of the phytochrome gene family in Pinus sylvestris and show that it includes not only functional genes but also pseudogenes. As expected, the functional PHYO does not appear to have evolved neutrally, while phytochrome pseudogenes show signs of unconstrained evolution.     

Rapid evolution of enormous, multichromosomal genomes in flowering plant mitochondria with exceptionally high mutation rates

Genome size and complexity vary tremendously among eukaryotic species and their organelles. Comparisons across deeply divergent eukaryotic lineages have suggested that variation in mutation rates may explain this diversity, with increased mutational burdens favoring reduced genome size and complexity. The discovery that mitochondrial mutation rates can differ by orders of magnitude among closely related angiosperm species presents a unique opportunity to test this hypothesis. We sequenced the mitochondrial genomes from two species in the angiosperm genus Silene with recent and dramatic accelerations in their mitochondrial mutation rates. Contrary to theoretical predictions, these genomes have experienced a massive proliferation of noncoding content. At 6.7 and 11.3 Mb, they are by far the largest known mitochondrial genomes, larger than most bacterial genomes and even some nuclear genomes. In contrast, two slowly evolving Silene mitochondrial genomes are smaller than average for angiosperms. Consequently, this genus captures approximately 98% of known variation in organelle genome size. The expanded genomes reveal several architectural changes, including the evolution of complex multichromosomal structures (with 59 and 128 circular-mapping chromosomes, ranging in size from 44 to 192 kb). They also exhibit a substantial reduction in recombination and gene conversion activity as measured by the relative frequency of alternative genome conformations and the level of sequence divergence between repeat copies. The evolution of mutation rate, genome size, and chromosome structure can therefore be extremely rapid and interrelated in ways not predicted by current evolutionary theories. Our results raise the hypothesis that changes in recombinational processes, including gene conversion, may be a central force driving the evolution of both mutation rate and genome structure.     

The standard genetic code enhances adaptive evolution of proteins

The standard genetic code, by which most organisms translate genetic material into protein metabolism, is non-randomly organized. The Error Minimization hypothesis interprets this non-randomness as an adaptation, proposing that natural selection produced a pattern of codon assignments that buffers genomes against the impact of mutations. Indeed, on the average any given point mutation has a lesser effect on the chemical properties of the utilized amino acid than expected by chance. Might it also, however, be the case that the non-random nature of the code effects the rate of adaptive evolution? To investigate this, here we develop population genetic simulations to test the rate of adaptive gene evolution under different genetic codes. We identify two independent properties of a genetic code that profoundly influence the speed of adaptive evolution. Noting that the standard genetic code exhibits both, we offer a new insight into the effects of the "error minimizing" code: such a code enhances the efficacy of adaptive sequence evolution.     

Mitochondrial Genetic Codes Evolve to Match Amino Acid Requirements of Proteins

Mitochondria often use genetic codes different from the standard genetic code. Now that many mitochondrial genomes have been sequenced, these variant codes provide the first opportunity to examine empirically the processes that produce new genetic codes. The key question is: Are codon reassignments the sole result of mutation and genetic drift? Or are they the result of natural selection? Here we present an analysis of 24 phylogenetically independent codon reassignments in mitochondria. Although the mutation-drift hypothesis can explain reassignments from stop to an amino acid, we found that it cannot explain reassignments from one amino acid to another. In particular—and contrary to the predictions of the mutation-drift hypothesis—the codon involved in such a reassignment was not rare in the ancestral genome. Instead, such reassignments appear to take place while the codon is in use at an appreciable frequency. Moreover, the comparison of inferred amino acid usage in the ancestral genome with the neutral expectation shows that the amino acid gaining the codon was selectively favored over the amino acid losing the codon. These results are consistent with a simple model of weak selection on the amino acid composition of proteins in which codon reassignments are selected because they compensate for multiple slightly deleterious mutations throughout the mitochondrial genome. We propose that the selection pressure is for reduced protein synthesis cost: most reassignments give amino acids that are less expensive to synthesize. Taken together, our results strongly suggest that mitochondrial genetic codes evolve to match the amino acid requirements of proteins.     

Increased Selection Response in Larger Populations. II. Selection for Ethanol Vapor Resistance in Drosophila Melanogaster at Two Population Sizes

The effect of large population size on selection response was investigated using Drosophila melanogaster, with four "small" lines of 160 selected parents/generation compared to two "large" lines of 1,600 selected parents/generation. All lines were selected under similar conditions at a selection intensity of approximately 0.55 standard deviations, for 65 generations, for increased ethanol vapor resistance (measured in minutes required to become anesthetized). Two unselected control lines of 320 parents/generation were also maintained. A significant effect of population size was found. The final treatment means and standard errors were: 27.91 +/- 1.28 min (two "large" lines); 19.40 +/- 1.54 min (four "small" lines); and 4.98 +/- 0.35 min (two control lines). To estimate the mutation rate for the trait, two isogenic lines of about 400 selected parents were selected for 29 generations. The mean increase in additive genetic variance per generation was 0.0009 times the initial environmental variance of the outbred lines. This is comparable to other reported mutation rates. Mutation can explain part of the difference in evolved resistance between treatments, but it appears that even at rather large population sizes, a large difference in long-term response can be obtained in larger outbred lines, from more complete utilization of the initial genetic variation.     

Mutational History of a Human Cell Lineage from Somatic to Induced Pluripotent Stem Cells

The accuracy of replicating the genetic code is fundamental. DNA repair mechanisms protect the fidelity of the genome ensuring a low error rate between generations. This sustains the similarity of individuals whilst providing a repertoire of variants for evolution. The mutation rate in the human genome has recently been measured to be 50–70 de novo single nucleotide variants (SNVs) between generations. During development mutations accumulate in somatic cells so that an organism is a mosaic. However, variation within a tissue and between tissues has not been analysed. By reprogramming somatic cells into induced pluripotent stem cells (iPSCs), their genomes and the associated mutational history are captured. By sequencing the genomes of polyclonal and monoclonal somatic cells and derived iPSCs we have determined the mutation rates and show how the patterns change from a somatic lineage in vivo through to iPSCs. Somatic cells have a mutation rate of 14 SNVs per cell per generation while iPSCs exhibited a ten-fold lower rate. Analyses of mutational signatures suggested that deamination of methylated cytosine may be the major mutagenic source in vivo, whilst oxidative DNA damage becomes dominant in vitro. Our results provide insights for better understanding of mutational processes and lineage relationships between human somatic cells. Furthermore it provides a foundation for interpretation of elevated mutation rates and patterns in cancer.     

Genetic drift and mutational hazard in the evolution of salamander genomic gigantism

Salamanders have the largest nuclear genomes among tetrapods and, excepting lungfishes, among vertebrates as a whole. Lynch and Conery (2003) have proposed the mutational‐hazard hypothesis to explain variation in genome size and complexity. Under this hypothesis, noncoding DNA imposes a selective cost by increasing the target for degenerative mutations (i.e., the mutational hazard). Expansion of noncoding DNA, and thus genome size, is driven by increased levels of genetic drift and/or decreased mutation rates; the former determines the efficiency with which purifying selection can remove excess DNA, whereas the latter determines the level of mutational hazard. Here, we test the hypothesis that salamanders have experienced stronger long‐term, persistent genetic drift than frogs, a related clade with more typically sized vertebrate genomes. To test this hypothesis, we compared dN/dS and Kr/Kc values of protein‐coding genes between these clades. Our results do not support this hypothesis; we find that salamanders have not experienced stronger genetic drift than frogs. Additionally, we find evidence consistent with a lower nucleotide substitution rate in salamanders. This result, along with previous work showing lower rates of small deletion and ectopic recombination in salamanders, suggests that a lower mutational hazard may contribute to genomic gigantism in this clade.     

Genome degradation is an ongoing process in Rickettsia.

To study reductive evolutionary processes in bacterial genomes, we examine sequences in the Rickettsia genomes which are unconstrained by selection and evolve as pseudogenes, one of which is the metK gene, which codes for AdoMet synthetase. Here, we sequenced the metK gene and three surrounding genes in eight different species of the genus Rickettsia. The metK gene was found to contain a high incidence of deletions in six lineages, while the three genes in its surroundings were functionally conserved in all eight lineages. A more drastic example of gene degradation was identified in the metK downstream region, which contained an open reading frame in Rickettsia felis. Remnants of this open reading frame could be reconstructed in five additional species by eliminating sites of frameshift mutations and termination codons. A detailed examination of the two reconstructed genes revealed that deletions strongly predominate over insertions and that there is a strong transition bias for point mutations which is coupled to an excess of GC-to-AT substitutions. Since the molecular evolution of these inactive genes should reflect the rates and patterns of neutral mutations, our results strongly suggest that there is a high spontaneous rate of deletions as well as a strong mutation bias toward AT pairs in the Rickettsia genomes. This may explain the low genomic G + C content (29%), the small genome size (1.1 Mb), and the high noncoding content (24%), as well as the presence of several pseudogenes in the Rickettsia prowazekii genome.     

Non-equivalent loci and mutation-selection balance

We consider the implications of mutationally non-equivalent loci for large populations of randomly mating diploid organisms under mutation-selection balance. Variation, across loci, of parameters such as the allelic mutational variance and the mutation rate, is shown to reduce the equilibrium genetic variance. This is proved to follow from the genetic variance contributed by a single locus having an underlying convexity. We give approximate results indicating the way small deviations of the mutational parameters, from their mean values, reduce the genetic variance. Numerical estimates of the size of the effect are given for more general variations of the parameters. Variation in the mutation rates has a significantly smaller effect than variation in the mutational variances. Under accepted parameter values, the reduction in genetic variance can be substantial.     

Quasi-species evolution in subdivided populations favours maximally deleterious mutations

Most models of quasi-species evolution predict that populations will evolve to occupy areas of sequence space with the greatest concentration of neutral sequences, thus minimizing the deleterious mutation rate and creating mutationally 'robust' genomes. In contrast, empirical studies of the principal model of quasi-species evolution, RNA viruses, suggest that the effects of deleterious mutations are more severe than in similar DNA-based microbes. We demonstrate that populations divided into discrete patches connected by dispersal may favour genotypes where the deleterious effect of non-neutral mutations is maximized. This effect is especially strong in the absence of back mutation and when the amount of time spent in hosts prior to dispersal is intermediate. Our results indicate that RNA viruses that produce acute infections initiated by a small number of virions are expected to evolve fragile genetic architectures when compared with other RNA viruses.